{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from pycaret.classification import setup, compare_models, create_model, tune_model, plot_model,predict_model, save_model, load_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 文件load\n",
    "csv_file = '../../datasets/diabetes.csv'\n",
    "diabetes = pd.read_csv(csv_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Setup Succesfully Completed!\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Description</th>        <th class=\"col_heading level0 col1\" >Value</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row0_col0\" class=\"data row0 col0\" >session_id</td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row0_col1\" class=\"data row0 col1\" >4630</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row1_col0\" class=\"data row1 col0\" >Target Type</td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row1_col1\" class=\"data row1 col1\" >Binary</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row2_col0\" class=\"data row2 col0\" >Label Encoded</td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row2_col1\" class=\"data row2 col1\" >0: 0, 1: 1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row3_col0\" class=\"data row3 col0\" >Original Data</td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row3_col1\" class=\"data row3 col1\" >(768, 9)</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row4_col0\" class=\"data row4 col0\" >Missing Values </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row4_col1\" class=\"data row4 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row5_col0\" class=\"data row5 col0\" >Numeric Features </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row5_col1\" class=\"data row5 col1\" >7</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row6_col0\" class=\"data row6 col0\" >Categorical Features </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row6_col1\" class=\"data row6 col1\" >1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row7_col0\" class=\"data row7 col0\" >Ordinal Features </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row7_col1\" class=\"data row7 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row8_col0\" class=\"data row8 col0\" >High Cardinality Features </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row8_col1\" class=\"data row8 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row9_col0\" class=\"data row9 col0\" >High Cardinality Method </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row9_col1\" class=\"data row9 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row10_col0\" class=\"data row10 col0\" >Sampled Data</td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row10_col1\" class=\"data row10 col1\" >(768, 9)</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row11_col0\" class=\"data row11 col0\" >Transformed Train Set</td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row11_col1\" class=\"data row11 col1\" >(537, 24)</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row12_col0\" class=\"data row12 col0\" >Transformed Test Set</td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row12_col1\" class=\"data row12 col1\" >(231, 24)</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row13_col0\" class=\"data row13 col0\" >Numeric Imputer </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row13_col1\" class=\"data row13 col1\" >mean</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row14_col0\" class=\"data row14 col0\" >Categorical Imputer </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row14_col1\" class=\"data row14 col1\" >constant</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row15_col0\" class=\"data row15 col0\" >Normalize </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row15_col1\" class=\"data row15 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row16_col0\" class=\"data row16 col0\" >Normalize Method </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row16_col1\" class=\"data row16 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row17_col0\" class=\"data row17 col0\" >Transformation </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row17_col1\" class=\"data row17 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row18_col0\" class=\"data row18 col0\" >Transformation Method </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row18_col1\" class=\"data row18 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row19_col0\" class=\"data row19 col0\" >PCA </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row19_col1\" class=\"data row19 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row20_col0\" class=\"data row20 col0\" >PCA Method </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row20_col1\" class=\"data row20 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row21_col0\" class=\"data row21 col0\" >PCA Components </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row21_col1\" class=\"data row21 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row22_col0\" class=\"data row22 col0\" >Ignore Low Variance </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row22_col1\" class=\"data row22 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row23_col0\" class=\"data row23 col0\" >Combine Rare Levels </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row23_col1\" class=\"data row23 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row24_col0\" class=\"data row24 col0\" >Rare Level Threshold </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row24_col1\" class=\"data row24 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row25_col0\" class=\"data row25 col0\" >Numeric Binning </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row25_col1\" class=\"data row25 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row26_col0\" class=\"data row26 col0\" >Remove Outliers </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row26_col1\" class=\"data row26 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row27_col0\" class=\"data row27 col0\" >Outliers Threshold </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row27_col1\" class=\"data row27 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row28_col0\" class=\"data row28 col0\" >Remove Multicollinearity </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row28_col1\" class=\"data row28 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row29_col0\" class=\"data row29 col0\" >Multicollinearity Threshold </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row29_col1\" class=\"data row29 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row30_col0\" class=\"data row30 col0\" >Clustering </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row30_col1\" class=\"data row30 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row31_col0\" class=\"data row31 col0\" >Clustering Iteration </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row31_col1\" class=\"data row31 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row32_col0\" class=\"data row32 col0\" >Polynomial Features </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row32_col1\" class=\"data row32 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row33_col0\" class=\"data row33 col0\" >Polynomial Degree </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row33_col1\" class=\"data row33 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row34_col0\" class=\"data row34 col0\" >Trignometry Features </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row34_col1\" class=\"data row34 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row35_col0\" class=\"data row35 col0\" >Polynomial Threshold </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row35_col1\" class=\"data row35 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row36_col0\" class=\"data row36 col0\" >Group Features </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row36_col1\" class=\"data row36 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row37_col0\" class=\"data row37 col0\" >Feature Selection </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row37_col1\" class=\"data row37 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row38_col0\" class=\"data row38 col0\" >Features Selection Threshold </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row38_col1\" class=\"data row38 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row39_col0\" class=\"data row39 col0\" >Feature Interaction </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row39_col1\" class=\"data row39 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row40_col0\" class=\"data row40 col0\" >Feature Ratio </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row40_col1\" class=\"data row40 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row41_col0\" class=\"data row41 col0\" >Interaction Threshold </td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row41_col1\" class=\"data row41 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row42_col0\" class=\"data row42 col0\" >Fix Imbalance</td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row42_col1\" class=\"data row42 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row43_col0\" class=\"data row43 col0\" >Fix Imbalance Method</td>\n",
       "                        <td id=\"T_7e98d2c0_127b_11eb_8b9e_54e1adcc3bd5row43_col1\" class=\"data row43 col1\" >SMOTE</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1907b1e1cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import model & initializing setup\n",
    "exp_name = setup(diabetes, target=diabetes.columns[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }</style><table id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Model</th>        <th class=\"col_heading level0 col1\" >Accuracy</th>        <th class=\"col_heading level0 col2\" >AUC</th>        <th class=\"col_heading level0 col3\" >Recall</th>        <th class=\"col_heading level0 col4\" >Prec.</th>        <th class=\"col_heading level0 col5\" >F1</th>        <th class=\"col_heading level0 col6\" >Kappa</th>        <th class=\"col_heading level0 col7\" >MCC</th>        <th class=\"col_heading level0 col8\" >TT (Sec)</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row0_col0\" class=\"data row0 col0\" >Logistic Regression</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row0_col1\" class=\"data row0 col1\" >0.7578</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row0_col2\" class=\"data row0 col2\" >0.8011</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row0_col3\" class=\"data row0 col3\" >0.5503</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row0_col4\" class=\"data row0 col4\" >0.7078</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row0_col5\" class=\"data row0 col5\" >0.6122</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row0_col6\" class=\"data row0 col6\" >0.4405</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row0_col7\" class=\"data row0 col7\" >0.4529</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row0_col8\" class=\"data row0 col8\" >0.0507</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row1_col0\" class=\"data row1 col0\" >Random Forest Classifier</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row1_col1\" class=\"data row1 col1\" >0.7578</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row1_col2\" class=\"data row1 col2\" >0.7828</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row1_col3\" class=\"data row1 col3\" >0.4968</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row1_col4\" class=\"data row1 col4\" >0.7376</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row1_col5\" class=\"data row1 col5\" >0.5848</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row1_col6\" class=\"data row1 col6\" >0.424</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row1_col7\" class=\"data row1 col7\" >0.4459</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row1_col8\" class=\"data row1 col8\" >0.131</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row2_col0\" class=\"data row2 col0\" >Ridge Classifier</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row2_col1\" class=\"data row2 col1\" >0.7522</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row2_col2\" class=\"data row2 col2\" >0</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row2_col3\" class=\"data row2 col3\" >0.5342</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row2_col4\" class=\"data row2 col4\" >0.6891</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row2_col5\" class=\"data row2 col5\" >0.5978</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row2_col6\" class=\"data row2 col6\" >0.4237</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row2_col7\" class=\"data row2 col7\" >0.4335</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row2_col8\" class=\"data row2 col8\" >0.0068</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row3_col0\" class=\"data row3 col0\" >Linear Discriminant Analysis</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row3_col1\" class=\"data row3 col1\" >0.7503</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row3_col2\" class=\"data row3 col2\" >0.802</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row3_col3\" class=\"data row3 col3\" >0.5339</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row3_col4\" class=\"data row3 col4\" >0.6839</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row3_col5\" class=\"data row3 col5\" >0.5962</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row3_col6\" class=\"data row3 col6\" >0.42</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row3_col7\" class=\"data row3 col7\" >0.4291</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row3_col8\" class=\"data row3 col8\" >0.0086</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row4_col0\" class=\"data row4 col0\" >CatBoost Classifier</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row4_col1\" class=\"data row4 col1\" >0.7485</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row4_col2\" class=\"data row4 col2\" >0.8199</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row4_col3\" class=\"data row4 col3\" >0.5664</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row4_col4\" class=\"data row4 col4\" >0.6784</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row4_col5\" class=\"data row4 col5\" >0.611</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row4_col6\" class=\"data row4 col6\" >0.4275</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row4_col7\" class=\"data row4 col7\" >0.4358</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row4_col8\" class=\"data row4 col8\" >2.431</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row5_col0\" class=\"data row5 col0\" >Gradient Boosting Classifier</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row5_col1\" class=\"data row5 col1\" >0.7468</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row5_col2\" class=\"data row5 col2\" >0.8107</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row5_col3\" class=\"data row5 col3\" >0.5769</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row5_col4\" class=\"data row5 col4\" >0.6598</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row5_col5\" class=\"data row5 col5\" >0.6105</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row5_col6\" class=\"data row5 col6\" >0.4251</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row5_col7\" class=\"data row5 col7\" >0.4309</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row5_col8\" class=\"data row5 col8\" >0.1457</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row6_col0\" class=\"data row6 col0\" >K Neighbors Classifier</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row6_col1\" class=\"data row6 col1\" >0.7448</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row6_col2\" class=\"data row6 col2\" >0.7625</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row6_col3\" class=\"data row6 col3\" >0.5506</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row6_col4\" class=\"data row6 col4\" >0.6748</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row6_col5\" class=\"data row6 col5\" >0.6018</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row6_col6\" class=\"data row6 col6\" >0.4169</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row6_col7\" class=\"data row6 col7\" >0.4252</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row6_col8\" class=\"data row6 col8\" >0.0119</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row7_col0\" class=\"data row7 col0\" >Extreme Gradient Boosting</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row7_col1\" class=\"data row7 col1\" >0.7447</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row7_col2\" class=\"data row7 col2\" >0.819</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row7_col3\" class=\"data row7 col3\" >0.5713</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row7_col4\" class=\"data row7 col4\" >0.6537</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row7_col5\" class=\"data row7 col5\" >0.606</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row7_col6\" class=\"data row7 col6\" >0.4193</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row7_col7\" class=\"data row7 col7\" >0.424</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row7_col8\" class=\"data row7 col8\" >0.0609</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row8_col0\" class=\"data row8 col0\" >Extra Trees Classifier</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row8_col1\" class=\"data row8 col1\" >0.7373</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row8_col2\" class=\"data row8 col2\" >0.7739</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row8_col3\" class=\"data row8 col3\" >0.481</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row8_col4\" class=\"data row8 col4\" >0.6797</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row8_col5\" class=\"data row8 col5\" >0.5592</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row8_col6\" class=\"data row8 col6\" >0.3804</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row8_col7\" class=\"data row8 col7\" >0.3944</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row8_col8\" class=\"data row8 col8\" >0.2234</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row9_col0\" class=\"data row9 col0\" >Light Gradient Boosting Machine</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row9_col1\" class=\"data row9 col1\" >0.7316</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row9_col2\" class=\"data row9 col2\" >0.8005</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row9_col3\" class=\"data row9 col3\" >0.5605</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row9_col4\" class=\"data row9 col4\" >0.6369</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row9_col5\" class=\"data row9 col5\" >0.5928</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row9_col6\" class=\"data row9 col6\" >0.394</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row9_col7\" class=\"data row9 col7\" >0.3986</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row9_col8\" class=\"data row9 col8\" >0.0735</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row10_col0\" class=\"data row10 col0\" >Ada Boost Classifier</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row10_col1\" class=\"data row10 col1\" >0.728</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row10_col2\" class=\"data row10 col2\" >0.8031</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row10_col3\" class=\"data row10 col3\" >0.5442</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row10_col4\" class=\"data row10 col4\" >0.6254</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row10_col5\" class=\"data row10 col5\" >0.5778</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row10_col6\" class=\"data row10 col6\" >0.3796</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row10_col7\" class=\"data row10 col7\" >0.3844</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row10_col8\" class=\"data row10 col8\" >0.1053</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col0\" class=\"data row11 col0\" >Decision Tree Classifier</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col1\" class=\"data row11 col1\" >0.7002</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col2\" class=\"data row11 col2\" >0.6681</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col3\" class=\"data row11 col3\" >0.562</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col4\" class=\"data row11 col4\" >0.5737</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col5\" class=\"data row11 col5\" >0.5641</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col6\" class=\"data row11 col6\" >0.3369</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col7\" class=\"data row11 col7\" >0.3393</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row11_col8\" class=\"data row11 col8\" >0.0077</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col0\" class=\"data row12 col0\" >Naive Bayes</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col1\" class=\"data row12 col1\" >0.6778</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col2\" class=\"data row12 col2\" >0.7367</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col3\" class=\"data row12 col3\" >0.2029</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col4\" class=\"data row12 col4\" >0.636</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col5\" class=\"data row12 col5\" >0.3029</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col6\" class=\"data row12 col6\" >0.1592</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col7\" class=\"data row12 col7\" >0.2066</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row12_col8\" class=\"data row12 col8\" >0.0057</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col0\" class=\"data row13 col0\" >SVM - Linear Kernel</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col1\" class=\"data row13 col1\" >0.5997</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col2\" class=\"data row13 col2\" >0</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col3\" class=\"data row13 col3\" >0.4114</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col4\" class=\"data row13 col4\" >0.4506</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col5\" class=\"data row13 col5\" >0.3405</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col6\" class=\"data row13 col6\" >0.1121</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col7\" class=\"data row13 col7\" >0.1406</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row13_col8\" class=\"data row13 col8\" >0.008</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col0\" class=\"data row14 col0\" >Quadratic Discriminant Analysis</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col1\" class=\"data row14 col1\" >0.5636</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col2\" class=\"data row14 col2\" >0.6078</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col3\" class=\"data row14 col3\" >0.4743</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col4\" class=\"data row14 col4\" >0.4644</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col5\" class=\"data row14 col5\" >0.4016</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col6\" class=\"data row14 col6\" >0.0926</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col7\" class=\"data row14 col7\" >0.1057</td>\n",
       "                        <td id=\"T_b175cdc0_127b_11eb_9f5d_54e1adcc3bd5row14_col8\" class=\"data row14 col8\" >0.0045</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x19069f692e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# best\n",
    "best = compare_models(sort='Accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "            text-align:  left;\n",
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       "            : ;\n",
       "            text-align:  left;\n",
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       "            : ;\n",
       "            text-align:  left;\n",
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       "            : ;\n",
       "            text-align:  left;\n",
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       "            : ;\n",
       "            text-align:  left;\n",
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       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row14_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
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       "            text-align:  left;\n",
       "        }</style><table id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Model</th>        <th class=\"col_heading level0 col1\" >Accuracy</th>        <th class=\"col_heading level0 col2\" >AUC</th>        <th class=\"col_heading level0 col3\" >Recall</th>        <th class=\"col_heading level0 col4\" >Prec.</th>        <th class=\"col_heading level0 col5\" >F1</th>        <th class=\"col_heading level0 col6\" >Kappa</th>        <th class=\"col_heading level0 col7\" >MCC</th>        <th class=\"col_heading level0 col8\" >TT (Sec)</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row0_col0\" class=\"data row0 col0\" >Logistic Regression</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row0_col1\" class=\"data row0 col1\" >0.7578</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row0_col2\" class=\"data row0 col2\" >0.8011</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row0_col3\" class=\"data row0 col3\" >0.5503</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row0_col4\" class=\"data row0 col4\" >0.7078</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row0_col5\" class=\"data row0 col5\" >0.6122</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row0_col6\" class=\"data row0 col6\" >0.4405</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row0_col7\" class=\"data row0 col7\" >0.4529</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row0_col8\" class=\"data row0 col8\" >0.0522</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row1_col0\" class=\"data row1 col0\" >Random Forest Classifier</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row1_col1\" class=\"data row1 col1\" >0.7578</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row1_col2\" class=\"data row1 col2\" >0.7828</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row1_col3\" class=\"data row1 col3\" >0.4968</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row1_col4\" class=\"data row1 col4\" >0.7376</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row1_col5\" class=\"data row1 col5\" >0.5848</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row1_col6\" class=\"data row1 col6\" >0.424</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row1_col7\" class=\"data row1 col7\" >0.4459</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row1_col8\" class=\"data row1 col8\" >0.1207</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row2_col0\" class=\"data row2 col0\" >Ridge Classifier</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row2_col1\" class=\"data row2 col1\" >0.7522</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row2_col2\" class=\"data row2 col2\" >0</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row2_col3\" class=\"data row2 col3\" >0.5342</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row2_col4\" class=\"data row2 col4\" >0.6891</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row2_col5\" class=\"data row2 col5\" >0.5978</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row2_col6\" class=\"data row2 col6\" >0.4237</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row2_col7\" class=\"data row2 col7\" >0.4335</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row2_col8\" class=\"data row2 col8\" >0.0073</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row3_col0\" class=\"data row3 col0\" >Linear Discriminant Analysis</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row3_col1\" class=\"data row3 col1\" >0.7503</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row3_col2\" class=\"data row3 col2\" >0.802</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row3_col3\" class=\"data row3 col3\" >0.5339</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row3_col4\" class=\"data row3 col4\" >0.6839</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row3_col5\" class=\"data row3 col5\" >0.5962</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row3_col6\" class=\"data row3 col6\" >0.42</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row3_col7\" class=\"data row3 col7\" >0.4291</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row3_col8\" class=\"data row3 col8\" >0.008</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row4_col0\" class=\"data row4 col0\" >CatBoost Classifier</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row4_col1\" class=\"data row4 col1\" >0.7485</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row4_col2\" class=\"data row4 col2\" >0.8199</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row4_col3\" class=\"data row4 col3\" >0.5664</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row4_col4\" class=\"data row4 col4\" >0.6784</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row4_col5\" class=\"data row4 col5\" >0.611</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row4_col6\" class=\"data row4 col6\" >0.4275</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row4_col7\" class=\"data row4 col7\" >0.4358</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row4_col8\" class=\"data row4 col8\" >2.519</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row5_col0\" class=\"data row5 col0\" >Gradient Boosting Classifier</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row5_col1\" class=\"data row5 col1\" >0.7468</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row5_col2\" class=\"data row5 col2\" >0.8107</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row5_col3\" class=\"data row5 col3\" >0.5769</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row5_col4\" class=\"data row5 col4\" >0.6598</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row5_col5\" class=\"data row5 col5\" >0.6105</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row5_col6\" class=\"data row5 col6\" >0.4251</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row5_col7\" class=\"data row5 col7\" >0.4309</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row5_col8\" class=\"data row5 col8\" >0.1429</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row6_col0\" class=\"data row6 col0\" >K Neighbors Classifier</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row6_col1\" class=\"data row6 col1\" >0.7448</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row6_col2\" class=\"data row6 col2\" >0.7625</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row6_col3\" class=\"data row6 col3\" >0.5506</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row6_col4\" class=\"data row6 col4\" >0.6748</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row6_col5\" class=\"data row6 col5\" >0.6018</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row6_col6\" class=\"data row6 col6\" >0.4169</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row6_col7\" class=\"data row6 col7\" >0.4252</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row6_col8\" class=\"data row6 col8\" >0.0112</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row7_col0\" class=\"data row7 col0\" >Extreme Gradient Boosting</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row7_col1\" class=\"data row7 col1\" >0.7447</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row7_col2\" class=\"data row7 col2\" >0.819</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row7_col3\" class=\"data row7 col3\" >0.5713</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row7_col4\" class=\"data row7 col4\" >0.6537</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row7_col5\" class=\"data row7 col5\" >0.606</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row7_col6\" class=\"data row7 col6\" >0.4193</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row7_col7\" class=\"data row7 col7\" >0.424</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row7_col8\" class=\"data row7 col8\" >0.0632</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row8_col0\" class=\"data row8 col0\" >Extra Trees Classifier</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row8_col1\" class=\"data row8 col1\" >0.7373</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row8_col2\" class=\"data row8 col2\" >0.7739</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row8_col3\" class=\"data row8 col3\" >0.481</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row8_col4\" class=\"data row8 col4\" >0.6797</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row8_col5\" class=\"data row8 col5\" >0.5592</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row8_col6\" class=\"data row8 col6\" >0.3804</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row8_col7\" class=\"data row8 col7\" >0.3944</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row8_col8\" class=\"data row8 col8\" >0.2085</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row9_col0\" class=\"data row9 col0\" >Light Gradient Boosting Machine</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row9_col1\" class=\"data row9 col1\" >0.7316</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row9_col2\" class=\"data row9 col2\" >0.8005</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row9_col3\" class=\"data row9 col3\" >0.5605</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row9_col4\" class=\"data row9 col4\" >0.6369</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row9_col5\" class=\"data row9 col5\" >0.5928</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row9_col6\" class=\"data row9 col6\" >0.394</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row9_col7\" class=\"data row9 col7\" >0.3986</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row9_col8\" class=\"data row9 col8\" >0.0728</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row10_col0\" class=\"data row10 col0\" >Ada Boost Classifier</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row10_col1\" class=\"data row10 col1\" >0.728</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row10_col2\" class=\"data row10 col2\" >0.8031</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row10_col3\" class=\"data row10 col3\" >0.5442</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row10_col4\" class=\"data row10 col4\" >0.6254</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row10_col5\" class=\"data row10 col5\" >0.5778</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row10_col6\" class=\"data row10 col6\" >0.3796</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row10_col7\" class=\"data row10 col7\" >0.3844</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row10_col8\" class=\"data row10 col8\" >0.1101</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row11_col0\" class=\"data row11 col0\" >Decision Tree Classifier</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row11_col1\" class=\"data row11 col1\" >0.7002</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row11_col2\" class=\"data row11 col2\" >0.6681</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row11_col3\" class=\"data row11 col3\" >0.562</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row11_col4\" class=\"data row11 col4\" >0.5737</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row11_col5\" class=\"data row11 col5\" >0.5641</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row11_col6\" class=\"data row11 col6\" >0.3369</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row11_col7\" class=\"data row11 col7\" >0.3393</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row11_col8\" class=\"data row11 col8\" >0.0074</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row12_col0\" class=\"data row12 col0\" >Naive Bayes</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row12_col1\" class=\"data row12 col1\" >0.6778</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row12_col2\" class=\"data row12 col2\" >0.7367</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row12_col3\" class=\"data row12 col3\" >0.2029</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row12_col4\" class=\"data row12 col4\" >0.636</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row12_col5\" class=\"data row12 col5\" >0.3029</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row12_col6\" class=\"data row12 col6\" >0.1592</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row12_col7\" class=\"data row12 col7\" >0.2066</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row12_col8\" class=\"data row12 col8\" >0.0051</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row13_col0\" class=\"data row13 col0\" >SVM - Linear Kernel</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row13_col1\" class=\"data row13 col1\" >0.5997</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row13_col2\" class=\"data row13 col2\" >0</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row13_col3\" class=\"data row13 col3\" >0.4114</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row13_col4\" class=\"data row13 col4\" >0.4506</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row13_col5\" class=\"data row13 col5\" >0.3405</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row13_col6\" class=\"data row13 col6\" >0.1121</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row13_col7\" class=\"data row13 col7\" >0.1406</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row13_col8\" class=\"data row13 col8\" >0.008</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row14_col0\" class=\"data row14 col0\" >Quadratic Discriminant Analysis</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row14_col1\" class=\"data row14 col1\" >0.5636</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row14_col2\" class=\"data row14 col2\" >0.6078</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row14_col3\" class=\"data row14 col3\" >0.4743</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row14_col4\" class=\"data row14 col4\" >0.4644</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row14_col5\" class=\"data row14 col5\" >0.4016</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row14_col6\" class=\"data row14 col6\" >0.0926</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row14_col7\" class=\"data row14 col7\" >0.1057</td>\n",
       "                        <td id=\"T_e61db3ac_127b_11eb_a657_54e1adcc3bd5row14_col8\" class=\"data row14 col8\" >0.0051</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1907b561eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# top 3\n",
    "top3 = compare_models(sort='Accuracy', n_select=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col2 {\n",
       "            background-color:  yellow;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col3 {\n",
       "            background-color:  yellow;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col0 {\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col1 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col2 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col3 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col4 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col5 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col6 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col7 {\n",
       "            : ;\n",
       "            text-align:  left;\n",
       "        }    #T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col8 {\n",
       "            background-color:  lightgrey;\n",
       "            text-align:  left;\n",
       "        }</style><table id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Model</th>        <th class=\"col_heading level0 col1\" >Accuracy</th>        <th class=\"col_heading level0 col2\" >AUC</th>        <th class=\"col_heading level0 col3\" >Recall</th>        <th class=\"col_heading level0 col4\" >Prec.</th>        <th class=\"col_heading level0 col5\" >F1</th>        <th class=\"col_heading level0 col6\" >Kappa</th>        <th class=\"col_heading level0 col7\" >MCC</th>        <th class=\"col_heading level0 col8\" >TT (Sec)</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row0_col0\" class=\"data row0 col0\" >Logistic Regression</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row0_col1\" class=\"data row0 col1\" >0.7578</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row0_col2\" class=\"data row0 col2\" >0.8011</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row0_col3\" class=\"data row0 col3\" >0.5503</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row0_col4\" class=\"data row0 col4\" >0.7078</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row0_col5\" class=\"data row0 col5\" >0.6122</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row0_col6\" class=\"data row0 col6\" >0.4405</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row0_col7\" class=\"data row0 col7\" >0.4529</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row0_col8\" class=\"data row0 col8\" >0.0548</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row1_col0\" class=\"data row1 col0\" >Random Forest Classifier</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row1_col1\" class=\"data row1 col1\" >0.7578</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row1_col2\" class=\"data row1 col2\" >0.7828</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row1_col3\" class=\"data row1 col3\" >0.4968</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row1_col4\" class=\"data row1 col4\" >0.7376</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row1_col5\" class=\"data row1 col5\" >0.5848</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row1_col6\" class=\"data row1 col6\" >0.424</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row1_col7\" class=\"data row1 col7\" >0.4459</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row1_col8\" class=\"data row1 col8\" >0.1273</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row2_col0\" class=\"data row2 col0\" >Ridge Classifier</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row2_col1\" class=\"data row2 col1\" >0.7522</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row2_col2\" class=\"data row2 col2\" >0</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row2_col3\" class=\"data row2 col3\" >0.5342</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row2_col4\" class=\"data row2 col4\" >0.6891</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row2_col5\" class=\"data row2 col5\" >0.5978</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row2_col6\" class=\"data row2 col6\" >0.4237</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row2_col7\" class=\"data row2 col7\" >0.4335</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row2_col8\" class=\"data row2 col8\" >0.007</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col0\" class=\"data row3 col0\" >Linear Discriminant Analysis</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col1\" class=\"data row3 col1\" >0.7503</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col2\" class=\"data row3 col2\" >0.802</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col3\" class=\"data row3 col3\" >0.5339</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col4\" class=\"data row3 col4\" >0.6839</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col5\" class=\"data row3 col5\" >0.5962</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col6\" class=\"data row3 col6\" >0.42</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col7\" class=\"data row3 col7\" >0.4291</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row3_col8\" class=\"data row3 col8\" >0.0083</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col0\" class=\"data row4 col0\" >CatBoost Classifier</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col1\" class=\"data row4 col1\" >0.7485</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col2\" class=\"data row4 col2\" >0.8199</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col3\" class=\"data row4 col3\" >0.5664</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col4\" class=\"data row4 col4\" >0.6784</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col5\" class=\"data row4 col5\" >0.611</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col6\" class=\"data row4 col6\" >0.4275</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col7\" class=\"data row4 col7\" >0.4358</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row4_col8\" class=\"data row4 col8\" >2.498</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col0\" class=\"data row5 col0\" >Gradient Boosting Classifier</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col1\" class=\"data row5 col1\" >0.7468</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col2\" class=\"data row5 col2\" >0.8107</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col3\" class=\"data row5 col3\" >0.5769</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col4\" class=\"data row5 col4\" >0.6598</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col5\" class=\"data row5 col5\" >0.6105</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col6\" class=\"data row5 col6\" >0.4251</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col7\" class=\"data row5 col7\" >0.4309</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row5_col8\" class=\"data row5 col8\" >0.1445</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col0\" class=\"data row6 col0\" >K Neighbors Classifier</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col1\" class=\"data row6 col1\" >0.7448</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col2\" class=\"data row6 col2\" >0.7625</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col3\" class=\"data row6 col3\" >0.5506</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col4\" class=\"data row6 col4\" >0.6748</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col5\" class=\"data row6 col5\" >0.6018</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col6\" class=\"data row6 col6\" >0.4169</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col7\" class=\"data row6 col7\" >0.4252</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row6_col8\" class=\"data row6 col8\" >0.0105</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col0\" class=\"data row7 col0\" >Extreme Gradient Boosting</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col1\" class=\"data row7 col1\" >0.7447</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col2\" class=\"data row7 col2\" >0.819</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col3\" class=\"data row7 col3\" >0.5713</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col4\" class=\"data row7 col4\" >0.6537</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col5\" class=\"data row7 col5\" >0.606</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col6\" class=\"data row7 col6\" >0.4193</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col7\" class=\"data row7 col7\" >0.424</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row7_col8\" class=\"data row7 col8\" >0.0654</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col0\" class=\"data row8 col0\" >Extra Trees Classifier</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col1\" class=\"data row8 col1\" >0.7373</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col2\" class=\"data row8 col2\" >0.7739</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col3\" class=\"data row8 col3\" >0.481</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col4\" class=\"data row8 col4\" >0.6797</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col5\" class=\"data row8 col5\" >0.5592</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col6\" class=\"data row8 col6\" >0.3804</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col7\" class=\"data row8 col7\" >0.3944</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row8_col8\" class=\"data row8 col8\" >0.1761</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col0\" class=\"data row9 col0\" >Light Gradient Boosting Machine</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col1\" class=\"data row9 col1\" >0.7316</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col2\" class=\"data row9 col2\" >0.8005</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col3\" class=\"data row9 col3\" >0.5605</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col4\" class=\"data row9 col4\" >0.6369</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col5\" class=\"data row9 col5\" >0.5928</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col6\" class=\"data row9 col6\" >0.394</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col7\" class=\"data row9 col7\" >0.3986</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row9_col8\" class=\"data row9 col8\" >0.0751</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col0\" class=\"data row10 col0\" >Ada Boost Classifier</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col1\" class=\"data row10 col1\" >0.728</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col2\" class=\"data row10 col2\" >0.8031</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col3\" class=\"data row10 col3\" >0.5442</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col4\" class=\"data row10 col4\" >0.6254</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col5\" class=\"data row10 col5\" >0.5778</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col6\" class=\"data row10 col6\" >0.3796</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col7\" class=\"data row10 col7\" >0.3844</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row10_col8\" class=\"data row10 col8\" >0.1073</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col0\" class=\"data row11 col0\" >Decision Tree Classifier</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col1\" class=\"data row11 col1\" >0.7002</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col2\" class=\"data row11 col2\" >0.6681</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col3\" class=\"data row11 col3\" >0.562</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col4\" class=\"data row11 col4\" >0.5737</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col5\" class=\"data row11 col5\" >0.5641</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col6\" class=\"data row11 col6\" >0.3369</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col7\" class=\"data row11 col7\" >0.3393</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row11_col8\" class=\"data row11 col8\" >0.0065</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col0\" class=\"data row12 col0\" >Naive Bayes</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col1\" class=\"data row12 col1\" >0.6778</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col2\" class=\"data row12 col2\" >0.7367</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col3\" class=\"data row12 col3\" >0.2029</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col4\" class=\"data row12 col4\" >0.636</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col5\" class=\"data row12 col5\" >0.3029</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col6\" class=\"data row12 col6\" >0.1592</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col7\" class=\"data row12 col7\" >0.2066</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row12_col8\" class=\"data row12 col8\" >0.0054</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col0\" class=\"data row13 col0\" >SVM - Linear Kernel</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col1\" class=\"data row13 col1\" >0.5997</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col2\" class=\"data row13 col2\" >0</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col3\" class=\"data row13 col3\" >0.4114</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col4\" class=\"data row13 col4\" >0.4506</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col5\" class=\"data row13 col5\" >0.3405</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col6\" class=\"data row13 col6\" >0.1121</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col7\" class=\"data row13 col7\" >0.1406</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row13_col8\" class=\"data row13 col8\" >0.0077</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col0\" class=\"data row14 col0\" >Quadratic Discriminant Analysis</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col1\" class=\"data row14 col1\" >0.5636</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col2\" class=\"data row14 col2\" >0.6078</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col3\" class=\"data row14 col3\" >0.4743</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col4\" class=\"data row14 col4\" >0.4644</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col5\" class=\"data row14 col5\" >0.4016</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col6\" class=\"data row14 col6\" >0.0926</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col7\" class=\"data row14 col7\" >0.1057</td>\n",
       "                        <td id=\"T_1b07c84c_127c_11eb_b18c_54e1adcc3bd5row14_col8\" class=\"data row14 col8\" >0.0051</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1907b5abb00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "                   intercept_scaling=1, l1_ratio=None, max_iter=100,\n",
       "                   multi_class='auto', n_jobs=None, penalty='l2',\n",
       "                   random_state=4630, solver='lbfgs', tol=0.0001, verbose=0,\n",
       "                   warm_start=False)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_models()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
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       "            background:  yellow;\n",
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       "            background:  yellow;\n",
       "        }    #T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col3 {\n",
       "            background:  yellow;\n",
       "        }    #T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col4 {\n",
       "            background:  yellow;\n",
       "        }    #T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col5 {\n",
       "            background:  yellow;\n",
       "        }    #T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col6 {\n",
       "            background:  yellow;\n",
       "        }</style><table id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Accuracy</th>        <th class=\"col_heading level0 col1\" >AUC</th>        <th class=\"col_heading level0 col2\" >Recall</th>        <th class=\"col_heading level0 col3\" >Prec.</th>        <th class=\"col_heading level0 col4\" >F1</th>        <th class=\"col_heading level0 col5\" >Kappa</th>        <th class=\"col_heading level0 col6\" >MCC</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row0_col0\" class=\"data row0 col0\" >0.8333</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row0_col1\" class=\"data row0 col1\" >0.9368</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row0_col2\" class=\"data row0 col2\" >0.5263</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row0_col3\" class=\"data row0 col3\" >1</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row0_col4\" class=\"data row0 col4\" >0.6897</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row0_col5\" class=\"data row0 col5\" >0.5902</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row0_col6\" class=\"data row0 col6\" >0.647</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row1_col0\" class=\"data row1 col0\" >0.7407</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row1_col1\" class=\"data row1 col1\" >0.8797</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row1_col2\" class=\"data row1 col2\" >0.5789</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row1_col3\" class=\"data row1 col3\" >0.6471</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row1_col4\" class=\"data row1 col4\" >0.6111</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row1_col5\" class=\"data row1 col5\" >0.4176</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row1_col6\" class=\"data row1 col6\" >0.419</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row2_col0\" class=\"data row2 col0\" >0.7407</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row2_col1\" class=\"data row2 col1\" >0.815</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row2_col2\" class=\"data row2 col2\" >0.6842</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row2_col3\" class=\"data row2 col3\" >0.619</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row2_col4\" class=\"data row2 col4\" >0.65</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row2_col5\" class=\"data row2 col5\" >0.4449</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row2_col6\" class=\"data row2 col6\" >0.4463</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row3_col0\" class=\"data row3 col0\" >0.7407</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row3_col1\" class=\"data row3 col1\" >0.7263</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row3_col2\" class=\"data row3 col2\" >0.4211</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row3_col3\" class=\"data row3 col3\" >0.7273</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row3_col4\" class=\"data row3 col4\" >0.5333</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row3_col5\" class=\"data row3 col5\" >0.371</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row3_col6\" class=\"data row3 col6\" >0.3976</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row4_col0\" class=\"data row4 col0\" >0.7407</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row4_col1\" class=\"data row4 col1\" >0.7624</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row4_col2\" class=\"data row4 col2\" >0.5263</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row4_col3\" class=\"data row4 col3\" >0.6667</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row4_col4\" class=\"data row4 col4\" >0.5882</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row4_col5\" class=\"data row4 col5\" >0.4028</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row4_col6\" class=\"data row4 col6\" >0.4088</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row5_col0\" class=\"data row5 col0\" >0.7778</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row5_col1\" class=\"data row5 col1\" >0.794</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row5_col2\" class=\"data row5 col2\" >0.5789</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row5_col3\" class=\"data row5 col3\" >0.7333</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row5_col4\" class=\"data row5 col4\" >0.6471</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row5_col5\" class=\"data row5 col5\" >0.4882</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row5_col6\" class=\"data row5 col6\" >0.4954</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row6_col0\" class=\"data row6 col0\" >0.7778</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row6_col1\" class=\"data row6 col1\" >0.782</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row6_col2\" class=\"data row6 col2\" >0.6316</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row6_col3\" class=\"data row6 col3\" >0.7059</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row6_col4\" class=\"data row6 col4\" >0.6667</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row6_col5\" class=\"data row6 col5\" >0.5008</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row6_col6\" class=\"data row6 col6\" >0.5025</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row7_col0\" class=\"data row7 col0\" >0.7736</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row7_col1\" class=\"data row7 col1\" >0.827</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row7_col2\" class=\"data row7 col2\" >0.5</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row7_col3\" class=\"data row7 col3\" >0.75</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row7_col4\" class=\"data row7 col4\" >0.6</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row7_col5\" class=\"data row7 col5\" >0.4508</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row7_col6\" class=\"data row7 col6\" >0.4688</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row8_col0\" class=\"data row8 col0\" >0.6981</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row8_col1\" class=\"data row8 col1\" >0.6968</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row8_col2\" class=\"data row8 col2\" >0.5</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row8_col3\" class=\"data row8 col3\" >0.5625</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row8_col4\" class=\"data row8 col4\" >0.5294</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row8_col5\" class=\"data row8 col5\" >0.3083</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row8_col6\" class=\"data row8 col6\" >0.3095</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row9_col0\" class=\"data row9 col0\" >0.7547</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row9_col1\" class=\"data row9 col1\" >0.7905</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row9_col2\" class=\"data row9 col2\" >0.5556</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row9_col3\" class=\"data row9 col3\" >0.6667</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row9_col4\" class=\"data row9 col4\" >0.6061</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row9_col5\" class=\"data row9 col5\" >0.4301</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row9_col6\" class=\"data row9 col6\" >0.4339</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col0\" class=\"data row10 col0\" >0.7578</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col1\" class=\"data row10 col1\" >0.8011</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col2\" class=\"data row10 col2\" >0.5503</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col3\" class=\"data row10 col3\" >0.7078</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col4\" class=\"data row10 col4\" >0.6122</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col5\" class=\"data row10 col5\" >0.4405</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row10_col6\" class=\"data row10 col6\" >0.4529</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5level0_row11\" class=\"row_heading level0 row11\" >SD</th>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row11_col0\" class=\"data row11 col0\" >0.0339</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row11_col1\" class=\"data row11 col1\" >0.0663</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row11_col2\" class=\"data row11 col2\" >0.0701</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row11_col3\" class=\"data row11 col3\" >0.1115</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row11_col4\" class=\"data row11 col4\" >0.0504</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row11_col5\" class=\"data row11 col5\" >0.0727</td>\n",
       "                        <td id=\"T_4ad9e338_127c_11eb_942a_54e1adcc3bd5row11_col6\" class=\"data row11 col6\" >0.0833</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1907dc562e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
      "                   intercept_scaling=1, l1_ratio=None, max_iter=100,\n",
      "                   multi_class='auto', n_jobs=None, penalty='l2',\n",
      "                   random_state=4630, solver='lbfgs', tol=0.0001, verbose=0,\n",
      "                   warm_start=False)\n"
     ]
    }
   ],
   "source": [
    "lr_classifier = create_model('lr')\n",
    "print(lr_classifier)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        }    #T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row10_col6 {\n",
       "            background:  yellow;\n",
       "        }</style><table id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Accuracy</th>        <th class=\"col_heading level0 col1\" >AUC</th>        <th class=\"col_heading level0 col2\" >Recall</th>        <th class=\"col_heading level0 col3\" >Prec.</th>        <th class=\"col_heading level0 col4\" >F1</th>        <th class=\"col_heading level0 col5\" >Kappa</th>        <th class=\"col_heading level0 col6\" >MCC</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row0_col0\" class=\"data row0 col0\" >0.8333</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row0_col1\" class=\"data row0 col1\" >0.9459</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row0_col2\" class=\"data row0 col2\" >0.7895</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row0_col3\" class=\"data row0 col3\" >0.75</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row0_col4\" class=\"data row0 col4\" >0.7692</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row0_col5\" class=\"data row0 col5\" >0.6389</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row0_col6\" class=\"data row0 col6\" >0.6394</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row1_col0\" class=\"data row1 col0\" >0.7593</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row1_col1\" class=\"data row1 col1\" >0.8812</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row1_col2\" class=\"data row1 col2\" >0.7895</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row1_col3\" class=\"data row1 col3\" >0.625</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row1_col4\" class=\"data row1 col4\" >0.6977</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row1_col5\" class=\"data row1 col5\" >0.5021</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row1_col6\" class=\"data row1 col6\" >0.5116</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row2_col0\" class=\"data row2 col0\" >0.7407</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row2_col1\" class=\"data row2 col1\" >0.8135</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row2_col2\" class=\"data row2 col2\" >0.8421</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row2_col3\" class=\"data row2 col3\" >0.5926</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row2_col4\" class=\"data row2 col4\" >0.6957</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row2_col5\" class=\"data row2 col5\" >0.4815</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row2_col6\" class=\"data row2 col6\" >0.5041</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row3_col0\" class=\"data row3 col0\" >0.7222</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row3_col1\" class=\"data row3 col1\" >0.7308</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row3_col2\" class=\"data row3 col2\" >0.5263</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row3_col3\" class=\"data row3 col3\" >0.625</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row3_col4\" class=\"data row3 col4\" >0.5714</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row3_col5\" class=\"data row3 col5\" >0.3682</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row3_col6\" class=\"data row3 col6\" >0.3711</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row4_col0\" class=\"data row4 col0\" >0.7037</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row4_col1\" class=\"data row4 col1\" >0.7579</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row4_col2\" class=\"data row4 col2\" >0.5789</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row4_col3\" class=\"data row4 col3\" >0.5789</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row4_col4\" class=\"data row4 col4\" >0.5789</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row4_col5\" class=\"data row4 col5\" >0.3504</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row4_col6\" class=\"data row4 col6\" >0.3504</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row5_col0\" class=\"data row5 col0\" >0.7778</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row5_col1\" class=\"data row5 col1\" >0.8165</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row5_col2\" class=\"data row5 col2\" >0.6842</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row5_col3\" class=\"data row5 col3\" >0.6842</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row5_col4\" class=\"data row5 col4\" >0.6842</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row5_col5\" class=\"data row5 col5\" >0.5128</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row5_col6\" class=\"data row5 col6\" >0.5128</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row6_col0\" class=\"data row6 col0\" >0.6296</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row6_col1\" class=\"data row6 col1\" >0.7549</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row6_col2\" class=\"data row6 col2\" >0.6842</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row6_col3\" class=\"data row6 col3\" >0.4815</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row6_col4\" class=\"data row6 col4\" >0.5652</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row6_col5\" class=\"data row6 col5\" >0.2593</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row6_col6\" class=\"data row6 col6\" >0.2714</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row7_col0\" class=\"data row7 col0\" >0.7547</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row7_col1\" class=\"data row7 col1\" >0.8508</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row7_col2\" class=\"data row7 col2\" >0.6111</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row7_col3\" class=\"data row7 col3\" >0.6471</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row7_col4\" class=\"data row7 col4\" >0.6286</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row7_col5\" class=\"data row7 col5\" >0.4457</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row7_col6\" class=\"data row7 col6\" >0.4461</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row8_col0\" class=\"data row8 col0\" >0.6226</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row8_col1\" class=\"data row8 col1\" >0.7032</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row8_col2\" class=\"data row8 col2\" >0.5</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row8_col3\" class=\"data row8 col3\" >0.45</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row8_col4\" class=\"data row8 col4\" >0.4737</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row8_col5\" class=\"data row8 col5\" >0.1808</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row8_col6\" class=\"data row8 col6\" >0.1814</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row9_col0\" class=\"data row9 col0\" >0.6792</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row9_col1\" class=\"data row9 col1\" >0.7857</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row9_col2\" class=\"data row9 col2\" >0.6667</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row9_col3\" class=\"data row9 col3\" >0.5217</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row9_col4\" class=\"data row9 col4\" >0.5854</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row9_col5\" class=\"data row9 col5\" >0.3301</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row9_col6\" class=\"data row9 col6\" >0.3367</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row10_col0\" class=\"data row10 col0\" >0.7223</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row10_col1\" class=\"data row10 col1\" >0.804</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row10_col2\" class=\"data row10 col2\" >0.6673</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row10_col3\" class=\"data row10 col3\" >0.5956</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row10_col4\" class=\"data row10 col4\" >0.625</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row10_col5\" class=\"data row10 col5\" >0.407</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row10_col6\" class=\"data row10 col6\" >0.4125</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5level0_row11\" class=\"row_heading level0 row11\" >SD</th>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row11_col0\" class=\"data row11 col0\" >0.0624</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row11_col1\" class=\"data row11 col1\" >0.0699</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row11_col2\" class=\"data row11 col2\" >0.1095</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row11_col3\" class=\"data row11 col3\" >0.0872</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row11_col4\" class=\"data row11 col4\" >0.0822</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row11_col5\" class=\"data row11 col5\" >0.1283</td>\n",
       "                        <td id=\"T_8aa2291c_127c_11eb_b6e7_54e1adcc3bd5row11_col6\" class=\"data row11 col6\" >0.1286</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1907dc9f828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 调超参\n",
    "tuned_lr_classifier = tune_model(lr_classifier)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_model(tuned_lr_classifier)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Model</th>\n",
       "      <th>Accuracy</th>\n",
       "      <th>AUC</th>\n",
       "      <th>Recall</th>\n",
       "      <th>Prec.</th>\n",
       "      <th>F1</th>\n",
       "      <th>Kappa</th>\n",
       "      <th>MCC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Logistic Regression</td>\n",
       "      <td>0.7359</td>\n",
       "      <td>0.8081</td>\n",
       "      <td>0.7284</td>\n",
       "      <td>0.602</td>\n",
       "      <td>0.6592</td>\n",
       "      <td>0.4468</td>\n",
       "      <td>0.4522</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Model  Accuracy     AUC  Recall  Prec.      F1   Kappa  \\\n",
       "0  Logistic Regression    0.7359  0.8081  0.7284  0.602  0.6592  0.4468   \n",
       "\n",
       "      MCC  \n",
       "0  0.4522  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# predict\n",
    "pred = predict_model(tuned_lr_classifier)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "763    0\n",
      "764    0\n",
      "765    0\n",
      "766    1\n",
      "767    0\n",
      "Name: Class variable, dtype: int64\n",
      "    Label   Score\n",
      "0     NaN  0.4714\n",
      "1     NaN  0.4606\n",
      "2     NaN  0.3390\n",
      "3     NaN  0.3304\n",
      "4     NaN  0.1000\n",
      "763     0     NaN\n",
      "764     0     NaN\n",
      "765     0     NaN\n",
      "766     0     NaN\n",
      "767     0     NaN\n"
     ]
    }
   ],
   "source": [
    "test_data = diabetes.iloc[-5:]\n",
    "print(test_data['Class variable'])\n",
    "\n",
    "predictions = predict_model(tuned_lr_classifier, data = test_data[test_data.columns[: -1]])\n",
    "print(predictions[predictions.columns[-2:]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save a model\n",
    "# save_model(dtuned_lr_classifiert, 'tuned_lr_classifier')\n",
    "# load\n",
    "# dt_saved = load_model('tuned_lr_classifier')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Reference</th>\n",
       "      <th>Turbo</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>lr</th>\n",
       "      <td>Logistic Regression</td>\n",
       "      <td>sklearn.linear_model.LogisticRegression</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>knn</th>\n",
       "      <td>K Neighbors Classifier</td>\n",
       "      <td>sklearn.neighbors.KNeighborsClassifier</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nb</th>\n",
       "      <td>Naive Bayes</td>\n",
       "      <td>sklearn.naive_bayes.GaussianNB</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dt</th>\n",
       "      <td>Decision Tree Classifier</td>\n",
       "      <td>sklearn.tree.DecisionTreeClassifier</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>svm</th>\n",
       "      <td>SVM - Linear Kernel</td>\n",
       "      <td>sklearn.linear_model.SGDClassifier</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rbfsvm</th>\n",
       "      <td>SVM - Radial Kernel</td>\n",
       "      <td>sklearn.svm.SVC</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gpc</th>\n",
       "      <td>Gaussian Process Classifier</td>\n",
       "      <td>sklearn.gaussian_process.GPC</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mlp</th>\n",
       "      <td>MLP Classifier</td>\n",
       "      <td>sklearn.neural_network.MLPClassifier</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ridge</th>\n",
       "      <td>Ridge Classifier</td>\n",
       "      <td>sklearn.linear_model.RidgeClassifier</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rf</th>\n",
       "      <td>Random Forest Classifier</td>\n",
       "      <td>sklearn.ensemble.RandomForestClassifier</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>qda</th>\n",
       "      <td>Quadratic Discriminant Analysis</td>\n",
       "      <td>sklearn.discriminant_analysis.QDA</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ada</th>\n",
       "      <td>Ada Boost Classifier</td>\n",
       "      <td>sklearn.ensemble.AdaBoostClassifier</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gbc</th>\n",
       "      <td>Gradient Boosting Classifier</td>\n",
       "      <td>sklearn.ensemble.GradientBoostingClassifier</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lda</th>\n",
       "      <td>Linear Discriminant Analysis</td>\n",
       "      <td>sklearn.discriminant_analysis.LDA</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>et</th>\n",
       "      <td>Extra Trees Classifier</td>\n",
       "      <td>sklearn.ensemble.ExtraTreesClassifier</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>xgboost</th>\n",
       "      <td>Extreme Gradient Boosting</td>\n",
       "      <td>xgboost.readthedocs.io</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lightgbm</th>\n",
       "      <td>Light Gradient Boosting Machine</td>\n",
       "      <td>github.com/microsoft/LightGBM</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>catboost</th>\n",
       "      <td>CatBoost Classifier</td>\n",
       "      <td>catboost.ai</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Name  \\\n",
       "ID                                          \n",
       "lr                    Logistic Regression   \n",
       "knn                K Neighbors Classifier   \n",
       "nb                            Naive Bayes   \n",
       "dt               Decision Tree Classifier   \n",
       "svm                   SVM - Linear Kernel   \n",
       "rbfsvm                SVM - Radial Kernel   \n",
       "gpc           Gaussian Process Classifier   \n",
       "mlp                        MLP Classifier   \n",
       "ridge                    Ridge Classifier   \n",
       "rf               Random Forest Classifier   \n",
       "qda       Quadratic Discriminant Analysis   \n",
       "ada                  Ada Boost Classifier   \n",
       "gbc          Gradient Boosting Classifier   \n",
       "lda          Linear Discriminant Analysis   \n",
       "et                 Extra Trees Classifier   \n",
       "xgboost         Extreme Gradient Boosting   \n",
       "lightgbm  Light Gradient Boosting Machine   \n",
       "catboost              CatBoost Classifier   \n",
       "\n",
       "                                            Reference  Turbo  \n",
       "ID                                                            \n",
       "lr            sklearn.linear_model.LogisticRegression   True  \n",
       "knn            sklearn.neighbors.KNeighborsClassifier   True  \n",
       "nb                     sklearn.naive_bayes.GaussianNB   True  \n",
       "dt                sklearn.tree.DecisionTreeClassifier   True  \n",
       "svm                sklearn.linear_model.SGDClassifier   True  \n",
       "rbfsvm                                sklearn.svm.SVC  False  \n",
       "gpc                      sklearn.gaussian_process.GPC  False  \n",
       "mlp              sklearn.neural_network.MLPClassifier  False  \n",
       "ridge            sklearn.linear_model.RidgeClassifier   True  \n",
       "rf            sklearn.ensemble.RandomForestClassifier   True  \n",
       "qda                 sklearn.discriminant_analysis.QDA   True  \n",
       "ada               sklearn.ensemble.AdaBoostClassifier   True  \n",
       "gbc       sklearn.ensemble.GradientBoostingClassifier   True  \n",
       "lda                 sklearn.discriminant_analysis.LDA   True  \n",
       "et              sklearn.ensemble.ExtraTreesClassifier   True  \n",
       "xgboost                        xgboost.readthedocs.io   True  \n",
       "lightgbm                github.com/microsoft/LightGBM   True  \n",
       "catboost                                  catboost.ai   True  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get all models for classification\n",
    "from pycaret.classification import models\n",
    "models()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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